Final workshop

Objective of the workshop

The objective is to gather a community to discuss SuperIce results and more broadly to draw a picture and perspective on the use of AI in the sea ice.

Abstracts

Here is the list of speakers and their abstracts for the SuperIce workshop.

Name	Institution	Title
Julien BRAJARD	NERSC	Super-resolution of sea ice thickness using diffusion models
Yiguo WANG	NERSC	Impact of super resolution SIT data for seasonal sea ice predictions
Richard DAVY	NERSC	How do unresolved variations in sea ice thickness alter the surface energy balance in the Arctic in climate models
Alberto CARRASSI	Univ. Bologna	Using machine learning, data assimilation and their combination to improve a new generation of sea ice models
Tobias FINN	CEREA	Generative diffusion surrogates for sea-ice modelling
Are KVANUM	Met. Norway	Regional Sea Ice predictions in northern Norway, Svalbard and the Barents Sea using Deep Learning
Daniela FLOCCO	Univ. Napoli	A double speed road: melt pond modelling and observations
Anton KOROSOV	NERSC	Challenges with deriving sea ice roughness from SAR imagery using deep learning
Matilde BRANDT KREINER	DMI	Arctic sea Ice observations from satellite SAR and PMW data using deep learning
Johannes LOHSE	UiT	Sea Ice Mapping from SAR: An overview of methods and approaches developed during 8 years of CIRFA

Funding

SuperIce is a project lead by the Nansen Environmental and Remote Sensing Center. SuperIce is funded by the European Space Agency FutureEO programme and supervised by Φ-lab. Here is the ESA SuperIce project page. For any question regarding the workshop please contact julien.brajard@nersc.no and henrike.wilborn@nersc.no